DocumentCode :
288886
Title :
Invariant image recognition using triple correlations and neural networks
Author :
Tiraki, A. ; Delopoulos, A. ; Kollias, S.
Author_Institution :
Div. of Comput. Sci., Nat. Tech. Univ. of Athens, Greece
Volume :
6
fYear :
1994
fDate :
27 Jun- 2 Jul 1994
Firstpage :
4055
Abstract :
Triple-correlation-based image representations were previously (Delopoulos, Tirakis, and Kollias, 1994) combined with neural network architectures for deriving an invariant, with respect to translation, rotation and dilation, robust classification scheme. Efficient implementations are described in this paper, which reduce the computational complexity of the method. Hierarchical, multiresolution neural networks are proposed as an effective architecture for achieving this purpose
Keywords :
computational complexity; image recognition; image representation; neural nets; computational complexity; hierarchical multiresolution neural networks; invariant image recognition; neural network architectures; triple correlations; Computer architecture; Feature extraction; Higher order statistics; Image recognition; Image representation; Neural networks; Retina; Robustness; Signal resolution; Statistical distributions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
Type :
conf
DOI :
10.1109/ICNN.1994.374863
Filename :
374863
Link To Document :
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